Abstract: In this work, we derive two numerical schemes for
solving a class of nonlinear partial differential equations. The first
method is of second order accuracy in space and time directions, the
scheme is unconditionally stable using Von Neumann stability
analysis, the scheme produced a nonlinear block system where
Newton-s method is used to solve it. The second method is of fourth
order accuracy in space and second order in time. The method is
unconditionally stable and Newton's method is used to solve the
nonlinear block system obtained. The exact single soliton solution
and the conserved quantities are used to assess the accuracy and to
show the robustness of the schemes. The interaction of two solitary
waves for different parameters are also discussed.
Abstract: This paper presents a real time force sensing
instrument that is designed for human gait analysis purposes. It is
capable of recording and monitoring ground reaction forces exerted
by human foot during various activities such as walking, running and
jumping in real time. In overall, force sensing mat mainly consists of
three elements: the force sensing mat, signal conditioning circuit and
data acquisition device. Force sensing mat is the mat that contains an
array of force sensing elements. To control and process the incoming
signal from the force sensing mat, Force-Logger and Force-Reloader
are developed using National Instrument Labview. This paper
describes the architecture of the force sensing mat, signal
conditioning circuit and the real time streaming of the incoming data
from the force sensing mat. Additionally, a preliminary experiment
dataset is presented in this paper.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: This paper examines two policy spaces–the ARC and TVA–and their spatialized politics. The research observes that the regional concept informs public policy and can contribute to the formation of stable policy initiatives. Using the subsystem framework to understand the political viability of policy regimes, the authors conclude policy geographies that appeal to traditional definitions of regions are more stable over time. In contrast, geographies that fail to reflect pre-existing representations of space are engaged in more competitive subsystem politics. The paper demonstrates that the spatial practices of policy regions and their directional politics influence the political viability of programs. The paper concludes that policy spaces should institutionalize pre-existing geographies–not manufacture new ones.
Abstract: This paper develops the fiscal health index of 21 local
governments in Taiwan over the 1984 to 2010 period. A quantile
regression analysis was used to explore the extent that economic
variables, political budget cycles, and legislative checks and balances,
impact different quantiles of fiscal health index for a country over a
sample period of time. Our findings suggest that local governments at
the lower quantile are significantly benefited from political budget
cycles and the increase in central government revenues, while
legislative effective checks and balances and the increase in central
government expenditures have a significantly negative effect on local
fiscal health. When local governments are in the upper tail of the
distribution, legislative checks and balances and growth in
macroeconomics have significant and adverse effects on the fiscal
health of local governments. However, increases in central
government revenues have significant and positive effects on the
health status of local government in Taiwan.
Abstract: Self-propelled forage harvesters in the 850
horsepower range were tested over three years for fuel consumption,
throughput and quality of chop for corn silage. Cut length had a
significant effect on fuel consumption, throughput and some aspects
of chop quality. Measure cut length was often different than
theoretical length of cut. Where cut length was equivalent fuel
consumption and throughput were equivalent across brands.
Shortening cut length from 17 to 11mm increases fuel consumption
53 percent measured as Mg of silage harvested per gallon of fuel used
and a 42 percent decrease in capacity as tons of fresh material per
hour run time.
Abstract: Software complexity metrics are used to predict
critical information about reliability and maintainability of software
systems. Object oriented software development requires a different
approach to software complexity metrics. Object Oriented Software
Metrics can be broadly classified into static and dynamic metrics.
Static Metrics give information at the code level whereas dynamic
metrics provide information on the actual runtime. In this paper we
will discuss the various complexity metrics, and the comparison
between static and dynamic complexity.
Abstract: Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
Abstract: Levan, an exopolysaccharide, was produced by
Microbacterium laevaniformans and its yield was characterized as a
function of concentrations of date syrup, sucrose and the fermentation
time. The optimum condition for levan production from sucrose was
at concentration of 20% sucrose for 48 h and for date syrup was 25%
for 48 h. The results show that an increase in fermentation time
caused a decrease in the levan production at all concentrations of date
syrup tested. Under these conditions after 48 h in sucrose medium,
levan production reached 48.9 g/L and for date syrup reached 10.48
g/L . The effect of pH on the yield of the purified levan was examined
and the optimum pH for levan production was determined to be 6.0.
Levan was composed mainly of fructose residues when analyzed by
TLC and FT-IR spectroscopy. Date syrup is a cheap substrate widely
available in Iran and has potential for levan production. The thermal
stability of levan was assessed by Thermo Gravimetric Analysis
(TGA) that revealed the onset of decomposition near to 49°C for the
levan produced from sucrose and 51°C for the levan from date syrup.
DSC results showed a single Tg at 98°C for levan produced from
sucrose and 206 °C for levan from date syrup.
Abstract: The temporal nature of negative selection is an under exploited area. In a negative selection system, newly generated antibodies go through a maturing phase, and the survivors of the phase then wait to be activated by the incoming antigens after certain number of matches. These without having enough matches will age and die, while these with enough matches (i.e., being activated) will become active detectors. A currently active detector may also age and die if it cannot find any match in a pre-defined (lengthy) period of time. Therefore, what matters in a negative selection system is the dynamics of the involved parties in the current time window, not the whole time duration, which may be up to eternity. This property has the potential to define the uniqueness of negative selection in comparison with the other approaches. On the other hand, a negative selection system is only trained with “normal" data samples. It has to learn and discover unknown “abnormal" data patterns on the fly by itself. Consequently, it is more appreciate to utilize negation selection as a system for pattern discovery and recognition rather than just pattern recognition. In this paper, we study the potential of using negative selection in discovering unknown temporal patterns.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: Work stress causes the organizational work-life
imbalance of employees. Because of this imbalance, workers perform
with lower effort to finish assignments and thus an organization will
experience reduced productivity. In order to investigate the problem
of an organizational work-life imbalance, this qualitative case study
focuses on an organizational work-life imbalance among Thai
software developers in a German-owned company in Chiang Mai,
Thailand. In terms of knowledge management, fishbone diagram is
useful analysis tool to investigate the root causes of an organizational
work-life imbalance systematically in focus-group discussions.
Furthermore, fishbone diagram shows the relationship between
causes and effects clearly. It was found that an organizational worklife
imbalance among Thai software developers is influenced by
management team, work environment, and information tools used in
the company over time.
Abstract: Hierarchical high-level PNs (HHPNs) with time
versions are a useful tool to model systems in a variety of application
domains, ranging from logistics to complex workflows. This paper
addresses an application domain which is receiving more and more
attention: procedure that arranges the final inpatient charge in
payment-s office and their management. We shall prove that Petri net
based analysis is able to improve the delays during the procedure, in
order that inpatient charges could be more reliable and on time.
Abstract: The behavior of Radial Basis Function (RBF) Networks greatly depends on how the center points of the basis functions are selected. In this work we investigate the use of instance reduction techniques, originally developed to reduce the storage requirements of instance based learners, for this purpose. Five Instance-Based Reduction Techniques were used to determine the set of center points, and RBF networks were trained using these sets of centers. The performance of the RBF networks is studied in terms of classification accuracy and training time. The results obtained were compared with two Radial Basis Function Networks: RBF networks that use all instances of the training set as center points (RBF-ALL) and Probabilistic Neural Networks (PNN). The former achieves high classification accuracies and the latter requires smaller training time. Results showed that RBF networks trained using sets of centers located by noise-filtering techniques (ALLKNN and ENN) rather than pure reduction techniques produce the best results in terms of classification accuracy. The results show that these networks require smaller training time than that of RBF-ALL and higher classification accuracy than that of PNN. Thus, using ALLKNN and ENN to select center points gives better combination of classification accuracy and training time. Our experiments also show that using the reduced sets to train the networks is beneficial especially in the presence of noise in the original training sets.
Abstract: This paper compares the heuristic Global Search
Techniques; Genetic Algorithm, Particle Swarm Optimization,
Simulated Annealing, Generalized Pattern Search, genetic algorithm
hybridized with Nelder–Mead and Generalized pattern search
technique for tuning of fuzzy PID controller for Puma 560. Since the
actual control is in joint space ,inverse kinematics is used to generate
various joint angles correspoding to desired cartesian space
trajectory. Efficient dynamics and kinematics are modeled on Matlab
which takes very less simulation time. Performances of all the tuning
methods with and without disturbance are compared in terms of ITSE
in joint space and ISE in cartesian space for spiral trajectory tracking.
Genetic Algorithm hybridized with Generalized Pattern Search is
showing best performance.
Abstract: Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.
Abstract: Recently, many web services to provide information for public transport are developed and released. They are optimized for mobile devices such a smartphone. We are also developing better path planning system for route buses and trains called “Bus-Net"[1]. However these systems only provide paths and related information before the user start moving. So we propose a context aware navigation to change the way to support public transport users. If we go to somewhere using many kinds of public transport, we have to know how to use them. In addition, public transport is dynamic system, and these have different characteristic by type. So we need information at real-time. Therefore we suggest the system that can support on user-s state. It has a variety of ways to help public transport users by each state, like turn-by-turn navigation. Context aware navigation will be able to reduce anxiety for using public transport.
Abstract: The Economic factors are leading to the rise of
infrastructures provides software and computing facilities as a
service, known as cloud services or cloud computing. Cloud services
can provide efficiencies for application providers, both by limiting
up-front capital expenses, and by reducing the cost of ownership over
time. Such services are made available in a data center, using shared
commodity hardware for computation and storage. There is a varied
set of cloud services available today, including application services
(salesforce.com), storage services (Amazon S3), compute services
(Google App Engine, Amazon EC2) and data services (Amazon
SimpleDB, Microsoft SQL Server Data Services, Google-s Data
store). These services represent a variety of reformations of data
management architectures, and more are on the horizon.
Abstract: In the first part of this paper [6], a method to
determine Frenet apparatus of the space-like curves in Minkowski
space-time is presented. In this work, the mentioned method is
developed for the time-like curves in Minkowski space-time.
Additionally, an example of presented method is illustrated.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.